水声通信中基于小波变换的图像编码研究

提出了一种高误比特率传输条件下的图像编码方法，它适用于水声信道的图像传输。针对水下图像的特点，选取合适的小波基和变换参数对图像进行离散小波变换；依据小波系数的能量分布特性，对不同的子带采用不同的量化和定长编码，编码率为0．8比特／像素。水声通信试验表明，在传输误比特率达到10^-2时，仍能得到可接受的图像质量。     

基于WBCT变换的水下图像高效压缩方法

针对压缩效率和重建质量无法兼顾的问题,提出一种基于WBCT变换(Wavelet-based contourlet transform)的水下图像高效压缩算法。首先根据水下图像和人类视觉系统的特点,在WBCT变换域提出了一种改进的人眼最小可觉察失真(JND)模型,以自适应去除水下图像中的视觉冗余。然后,对重要的低频系数采用定长量化和无损压缩;而对高频系数,采用基于WBCT树结构的变精度定长量化和位置差降编码策略进行编码。实验结果表明,提出的算法不仅具有较高的压缩效率,而且能获得视觉上较为满意的解码效果,适用于水下图像在甚低比特率下的压缩传输。     

基于DSP的水下图像传输系统研究

本文研究了基于高性能的DSP芯片TMS320C549的水下图像传输系统，并采用Goertzel算法进行信源编码和MFSK调制方式、运用Turbo码进行信道的编、解码，来实现水下视频图像高速数据传输的目的。     

水下机器人视频图像高效压缩方法研究

水下视频图像压缩一直是有限带宽水声信道实时传输海量视频数据的关键技术之一。本文首先介绍了目前水下机器人和水下视频图像压缩研究存在的主要问题,并综合分析了目前几种高效视频压缩方法的特点并探讨了进一步研究的方向。此外,根据水下视频的成像特点,提出了高效的全局与局部运动混合补偿方案和基于小波变换的预处理方法。初步实验结果表明：本文提出的预处理方法可以有效去除视频图像中存在的大量视觉冗余和空间冗余,提出的混合运动补偿方案可以获得很高的压缩编码效率;但必须进一步研究快速、有效的全局运动估计方法。     

水声信道高速率数据传输技术

本文介绍近年来水声信道高速率数所传输技术的一些研究进展，并结合本所研究的水声数据遥测，数字语音通讯和视频图像传输实验样机，讨论了具有抗多途干扰的声传输系统在调制信号设计及信号处理上所采用的关键技术。     

水下彩色图像传输的信号调制及信道压缩编码设计研究

就水下彩色图像传输这一研究课题，提供了其调制和传输控制部分的DSP解决方案，详细分析了针对水声信道这一特殊传输介质，所采用的特殊调制方法和传输发送机理，并提供了硬件原理图及相应的软件算法流程。     

基于小波变换和零树法的水声信道彩色图像压缩编解码研究

基于小波变换和“改变了的”零树法编解码原理 ,结合水声信道的特点 ,构建了一个以 DSP为核心的图像处理系统。在不同压缩比的情况下 ,完成了对一幅 6 4× 6 4点阵的静态彩色图像数据的压缩和解压缩。当压缩比与传统的 JPEG算法的压缩比相近的情况下 ,解压缩后图像的总体观感效果有明显的改善 ,从而对在水声信道中传输彩色图像作出了积极的尝试     

基于声场模型的猎雷声呐探测成像仿真方法

针对猎雷声呐对水雷目标探测仿真问题,提出一种基于运动学信息与水下声场传播耦合分析的探测成像仿真方法。利用Bellhop3D声场分析方法对水下声信道信号冲击响应进行计算,结合信号复分析方法得到信号传播信道参数以构建声散射模型,以运动耦合方式综合分析声呐搭载平台位置、姿态及速度等因素对回波信号的影响,通过综合考虑上述因素来模拟目标回波信号,从而利用较为真实的等效回波信号进行图像重构。以高频前视声呐为例,对声呐探测沉底水雷目标情况进行了仿真,结果表明,该方法能够得到高频声呐对沉底水雷目标的探测图像,与实际情况具有一致性,可为进一步构建反水雷相关模拟仿真训练系统提供参考。     

基于分层图像复原的水下目标距离估计

水下目标的距离估计对于水下作业有着十分重要的意义。目前常用的距离估计方法无论是光测距还是声测距都对于设备有很大的依赖性,本文提出一种基于复原技术的距离估计方法,通过建立水下退化图像的分层复原模型并利用清晰度评价函数,根据对图像清晰复原时的参数估计实现目标距离估计。这种方法紧需要单幅水下图像就可实现目标整体距离估计。文中通过实验验证了该方法的有效性。     

数字式水声语音通信发射器系统的研制

利用纵振换能器的纵向振动与换能器前盖板的弯曲振动相耦合原理，采用纵振换能器与声反射器配合，研制出一种适应在复杂海洋声信道进行高速率传输，具有低频，宽带，大功率等优点的水声换能器。     

Low-bit-rate coding of underwater video using wavelet-basedcompression algorithms

Recent advances in autonomous underwater vehicle (AUV) and underwater communication technology have promoted a surge of research activity within the area of signal and information processing. A new application is proposed herein for capturing and processing underwater video onboard an untethered AUV, then transmitting it to a remote platform using acoustic telemetry. Since video communication requires a considerably larger bandwidth than that provided by an underwater acoustic channel, the data must be massively compressed prior to transmission from the AUV. Past research has shown that the low contrast and low-detailed nature of underwater imagery allows for low-bit-rate coding of the data by wavelet-based image-coding algorithms. In this work, these findings have been extended to the design of a wavelet-based hybrid video encoder which employs entropy-constrained vector quantization (ECVQ) with overlapped block-based motion compensation. The ECVQ codebooks were designed from a statistical source model which describes the distribution of high subband wavelet coefficients in both intraframe and prediction error images. Results indicate that good visual quality can be achieved for very low bit-rate coding of underwater video with our algorithm     

Recent advances in high-speed underwater acoustic communications

In recent years, underwater acoustic (UWA) communications have received much attention as their applications have begun to shift from military toward commercial. Digital communications through UWA channels differ substantially from those in other media, such as radio channels, due to severe signal degradations caused by multipath propagation and high temporal and spatial variability of the channel conditions. The design of underwater acoustic communication systems has until recently relied on the use of noncoherent modulation techniques. However, to achieve high data rates on the severely band-limited UWA channels, bandwidth-efficient modulation techniques must be considered, together with array processing for exploitation of spatial multipath diversity. The new generation of underwater communication systems, employing phase-coherent modulation techniques, has a potential of achieving at least an order of magnitude increase in data throughput. The emerging communication scenario in which the modern underwater acoustic systems mill operate is that of an underwater network consisting of stationary and mobile nodes. Current research focuses on the development of efficient signal processing algorithms, multiuser communications in the presence of interference, and design of efficient modulation and coding schemes. This paper presents a review of recent results and research problems in high-speed underwater acoustic communications, focusing on the bandwidth-efficient phase-coherent methods. Experimental results are included to illustrate the state-of-the-art coherent detection of digital signals transmitted at 30 and 40 kb/s through a rapidly varying one-mile shallow water channel     

A voting-based approach for fast object recognition in underwateracoustic images

This paper describes a voting-based approach for the fast automatic recognition of man-made objects and related attitude estimation in underwater acoustic images generated by forward-looking sonars or acoustic cameras. In general, the continuous analysis of sequences of images is a very heavy task for human operators and this is due to the poor quality of acoustic images. Hence, algorithms able to recognize an object on the basis of a priori knowledge of the model and to estimate its attitude with reference to a global coordinate system are very useful to facilitate underwater operations like object manipulation or vehicle navigation. The proposed method is capable of recognizing objects and estimating their two-dimensional attitude by using information coming from boundary segments and their angular relations. It is based on a simple voting approach directly applied to the edge discontinuities of underwater acoustic images, whose quality is usually affected by some undesired effects such as object blurring, speckle noise, and geometrical distortions degrading the edge detection. The voting approach is robust, with respect to these effects, so that good results are obtained even with images of very poor quality. The sequences of simulated and real acoustic images are presented in order to test the validity of the proposed method in terms of average estimation error and computational load     

A simulation involving MAPS video bandwidth reduction, acoustic channel errors, and error checking

The reliable acoustic transmission of images that have been processed by a video bandwidth reduction technique such as Micro-Adaptive Picture Sequencing (MAPS) necessitates a robust coding scheme. This is due to the fact that errors effect compressed data more seriously than uncompressed data. For this reason image quality is a function of three system variables: image compression, channel noise, and error checking. A real-time simulation has been developed to determine the relationship between the three system variables. The simulator uses two 68000 microcomputers connected by a serial link; one does image compression and noise modeling while the other performs error checking and image reconstruction. The noise model uses 17 characteristics and operating parameters of the acoustic channel to corrupt the image data with single bit random errors. At the receiver the error checking can correct up to 90 percent of the most serious single bit errors.     

Object detection and tracking method of AUV based on acoustic vision

This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.     

The state of the art in underwater acoustic telemetry

Progress in underwater acoustic telemetry since 1982 is reviewed within a framework of six current research areas: (1) underwater channel physics, channel simulations, and measurements; (2) receiver structures; (3) diversity exploitation; (4) error control coding; (5) networked systems; and (6) alternative modulation strategies. Advances in each of these areas as well as perspectives on the future challenges facing them are presented. A primary thesis of this paper is that increased integration of high-fidelity channel models into ongoing underwater telemetry research is needed if the performance envelope (defined in terms of range, rate, and channel complexity) of underwater modems is to expand     

一种基于平稳小波变换的海底管线边缘检测方法

海底影像存在着对比度低、噪声污染严重、图像质量差等问题,采用传统算子的海底管线边缘图像中含有大量的无用和断裂边缘信息。文中将多尺度边缘检测和匹配跟踪相结合,提出利用平稳小波变换的海底管线边缘检测方法;在提取边缘的同时利用匹配跟踪手段对噪声干扰进行抑制,提高图像目标边缘检测质量。通过对海底管线和测试图像边缘检测实验表明,文中所提出的方法在抑制图像噪声的干扰、提高水下目标边缘完整性方面明显优于传统的边缘提取算子,证明该算法的有效性。     

Spatial diversity equalization applied to underwater communications

Underwater acoustic digital communication is difficult because of the nature of the fading multipath channels. Digital signal processing, such as adaptive equalization, is known to greatly improve the communication data rate by limiting intersymbol interference (ISI). However, existing underwater acoustic equalization studies are limited to single-channel techniques, and spatial diversity processing is limited to selection or combining. In this paper, we design minimum mean-square error (MMSE) equalizers jointly among all spatial diversity channels. We call this spatial diversity equalization (SDE). Results are based on a very sparse vertical array in a midrange underwater acoustic channel. We study the effect of element number and placement, the length of the equalization filters, and linear feedforward versus nonlinear decision feedback algorithms. A suboptimum equalizer combiner (EC) is studied to alleviate the computational intensity of JCE. We first design the system for a known acoustic channel; later, some results are verified using adaptive algorithms. Results are presented both in terms of the mean-square error (MSE) and the probability of a symbol error. The latter is important as it is the ultimate interest for a digital communication system. We found that system performance improves rapidly with an increase in the number of spatial channels